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Artificially Intelligent Simulated Patients in Undergraduate Surgical Teaching: A Single Blinded Randomized
W Baraza1, Georgina Staples1, Cameron Wells1
1Faculty of Medical and Health Sciences, The University of Auckland, Auckland, Aotearoa New Zealand.
The Clinical Teacher
|July 30, 2026
Summary
Artificial intelligence simulated patients (AISP) are comparable to traditional methods for developing clinical reasoning skills in medical students. This AI approach may enhance academic performance and is welcomed in medical curricula.
Area of Science:
- Medical Education
- Artificial Intelligence in Healthcare
- Clinical Reasoning Development
Background:
- Self-directed learning (SDL) and reflection are crucial for clinicians.
- Limited evidence exists on using AI to support medical SDL.
- AI simulated patients (AISP) offer high-fidelity, reflective educational interactions.
Purpose of the Study:
- To compare SDL with AISP interaction versus standard SDL for developing clinical reasoning skills.
- To evaluate the effectiveness of AISP in undergraduate medical education.
Main Methods:
- Single-institution randomized controlled study with undergraduate students learning gallstone disease.
- Participants randomized to AISP intervention or standard educational resources.
- Standardized clinical skills assessment with quantitative and qualitative data collection.
Main Results:
- AISP group showed statistical noninferiority to the control group (13.1 vs. 12.1 assessment scores, p=0.11).
- Intervention group had significantly more distinction grades (6 vs. 1, p=0.037), suggesting improved clinical management.
- Qualitative data indicated high satisfaction and enthusiasm for AISPs.
Conclusions:
- AISPs are comparable to traditional resources for developing undergraduate clinical skills.
- AISPs may enhance academic performance in undergraduate surgery.
- AISPs show potential as a supplementary tool in medical curricula.
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01:11Blinding
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02:07Blind Procedures
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